Elamur Research⌕
☰
home / authors / Zhiwei Jiang

Zhiwei Jiang

Zhiwei Jiang has 4 papers in our library, in 2025, most of them on Language models & pretraining; often with Qing Gu, Yafeng Yin, Yuchen Fu.

4 papers in our library · 2025

OpenAlex · ORCID · h-index 20 · 148 works · 1,539 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 83 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7518

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 24 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. LocAgent: Graph-Guided LLM Agents for Code Localization (2025 · 27 citations)
    Code localization means finding the files, classes and functions that must be edited to resolve an issue. It is difficult because issue reports often describe symptoms rather than causes, and the relevant code may sit several dependency steps away. LocAgent addresses this by converting a Python repository into a…
  2. LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models (2025 · 16 citations)
    Large language models handle inputs poorly once these exceed the context length seen during pretraining. Continuing training on full-length sequences fixes this but is expensive, since attention cost grows quadratically with length. LongRecipe is a training framework that extends the context window without training…
  3. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs (2025 · 10 citations)
    Decoder-only LLMs rely on causal attention. When sentence embeddings are extracted from them without fine-tuning, tokens near the start of the input cannot see later tokens. Prompt-based methods such as PromptEOL read the embedding from the final prompt token, but that token still inherits the skewed representations…
  4. Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering (2025 · 8 citations)
    Large language models can produce sentence embeddings without any training data or fine-tuning: a prompt wraps the sentence, and the hidden state of the final token serves as the vector.

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. A Unified Target-Oriented Sequence-to-Sequence Model for Emotion-Cause Pair Extraction ↗IEEE/ACM Transactions on Audio Speech and Language Processing · no summary yetZifeng Cheng et al.2021 · 70 citations

 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); 23 citing papers with a page here →.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/zhiwei-jiang/